Augmented Lagrangian Tracking for distributed optimization with equality and inequality coupling constraints

In this paper we propose a novel Augmented Lagrangian Tracking distributed optimization algorithm for solving multi-agent optimization problems where each agent has its own decision variables, cost function and constraint set, and the goal is to minimize the sum of the agents’ cost functions subject...

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Published in:	Automatica (Oxford) Vol. 157; p. 111269
Main Authors:	Falsone, Alessandro, Prandini, Maria
Format:	Journal Article
Language:	English
Published:	Elsevier Ltd 01.11.2023
Subjects:	ADMM Augmented Lagrangian Constraint-coupled optimization Distributed optimization Proximal algorithm Distributed optimization ADMM Proximal algorithm Constraint-coupled optimization Augmented Lagrangian
ISSN:	0005-1098, 1873-2836
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Abstract	In this paper we propose a novel Augmented Lagrangian Tracking distributed optimization algorithm for solving multi-agent optimization problems where each agent has its own decision variables, cost function and constraint set, and the goal is to minimize the sum of the agents’ cost functions subject to local constraints plus some additional coupling constraint involving the decision variables of all the agents. In contrast to alternative approaches available in the literature, the proposed algorithm jointly features a constant penalty parameter, the ability to cope with unbounded local constraint sets, and the ability to handle both affine equality and nonlinear inequality coupling constraints, while requiring convexity only. The effectiveness of the approach is shown first on an artificial example with complexity features that make other state-of-the-art algorithms not applicable and then on a realistic example involving the optimization of the charging schedule of a fleet of electric vehicles.
AbstractList	In this paper we propose a novel Augmented Lagrangian Tracking distributed optimization algorithm for solving multi-agent optimization problems where each agent has its own decision variables, cost function and constraint set, and the goal is to minimize the sum of the agents’ cost functions subject to local constraints plus some additional coupling constraint involving the decision variables of all the agents. In contrast to alternative approaches available in the literature, the proposed algorithm jointly features a constant penalty parameter, the ability to cope with unbounded local constraint sets, and the ability to handle both affine equality and nonlinear inequality coupling constraints, while requiring convexity only. The effectiveness of the approach is shown first on an artificial example with complexity features that make other state-of-the-art algorithms not applicable and then on a realistic example involving the optimization of the charging schedule of a fleet of electric vehicles.
ArticleNumber	111269
Author	Prandini, Maria Falsone, Alessandro
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Cites_doi	10.1109/TCNS.2017.2698261 10.1109/TAC.2010.2041686 10.1109/TAC.2017.2747505 10.1109/TSP.2013.2254478 10.1109/LCSYS.2020.3001427 10.1109/TAC.2008.2009515 10.1109/TAC.2014.2308612 10.1002/rnc.6048 10.1016/j.automatica.2021.109938 10.1109/TAC.2011.2167817 10.1016/j.automatica.2017.07.003 10.1016/j.automatica.2016.01.006 10.1016/j.automatica.2020.108962 10.1109/MCS.2019.2900783 10.1016/j.automatica.2021.109738 10.1109/TCNS.2019.2925267 10.1137/16M1084316 10.2140/pjm.1967.21.343 10.1016/j.automatica.2009.10.021 10.1109/TSP.2016.2544743 10.1109/TSP.2021.3123888 10.1109/TAC.2019.2912494
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Keywords	Distributed optimization ADMM Proximal algorithm Constraint-coupled optimization Augmented Lagrangian
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References	Sinkhorn, Knopp (b21) 1967; 21 Mota, Xavier, Aguiar, Püschel (b13) 2013; 61 Zhu, Martínez (b25) 2010; 46 Qu, Li (b18) 2018; 5 Falsone, Prandini (b9) 2022; 135 Nedić, Ozdaglar, Parrilo (b16) 2010; 55 Romao, Margellos, Notarstefano, Papachristodoulou (b20) 2021; 131 Wang, Hu (b24) 2022; 32 Falsone, Prandini (b8) 2020; 5 Falsone, Margellos, Garatti, Prandini (b6) 2017; 84 Kia, Van Scoy, Cortes, Freeman, Lynch, Martinez (b10) 2019; 39 Su, Wang, Sun (b22) 2021; 70 Vujanic, Esfahani, Goulart, Mariéthoz, Morari (b23) 2016; 67 Bertsekas (b2) 2015 Nedić, Ozdaglar (b15) 2009; 54 Nedić, Olshevsky, Shi (b14) 2017; 27 Rockafellar (b19) 1970 Notarnicola, Notarstefano (b17) 2020; 7 Chang, Nedić, Scaglione (b5) 2014; 59 Zhu, Martínez (b26) 2012; 57 Liang, Wang, Yin (b11) 2020; 63 Bertsekas (b1) 1999 Bertsekas, Tsitsiklis (b3) 1989 Chang (b4) 2016; 64 Margellos, Falsone, Garatti, Prandini (b12) 2018; 63 Falsone, Notarnicola, Notarstefano, Prandini (b7) 2020; 117 Chang (10.1016/j.automatica.2023.111269_b5) 2014; 59 Liang (10.1016/j.automatica.2023.111269_b11) 2020; 63 Nedić (10.1016/j.automatica.2023.111269_b14) 2017; 27 Wang (10.1016/j.automatica.2023.111269_b24) 2022; 32 Bertsekas (10.1016/j.automatica.2023.111269_b3) 1989 Kia (10.1016/j.automatica.2023.111269_b10) 2019; 39 Falsone (10.1016/j.automatica.2023.111269_b6) 2017; 84 Zhu (10.1016/j.automatica.2023.111269_b25) 2010; 46 Falsone (10.1016/j.automatica.2023.111269_b9) 2022; 135 Mota (10.1016/j.automatica.2023.111269_b13) 2013; 61 Bertsekas (10.1016/j.automatica.2023.111269_b1) 1999 Bertsekas (10.1016/j.automatica.2023.111269_b2) 2015 Romao (10.1016/j.automatica.2023.111269_b20) 2021; 131 Su (10.1016/j.automatica.2023.111269_b22) 2021; 70 Chang (10.1016/j.automatica.2023.111269_b4) 2016; 64 Zhu (10.1016/j.automatica.2023.111269_b26) 2012; 57 Vujanic (10.1016/j.automatica.2023.111269_b23) 2016; 67 Falsone (10.1016/j.automatica.2023.111269_b7) 2020; 117 Nedić (10.1016/j.automatica.2023.111269_b16) 2010; 55 Rockafellar (10.1016/j.automatica.2023.111269_b19) 1970 Nedić (10.1016/j.automatica.2023.111269_b15) 2009; 54 Falsone (10.1016/j.automatica.2023.111269_b8) 2020; 5 Margellos (10.1016/j.automatica.2023.111269_b12) 2018; 63 Qu (10.1016/j.automatica.2023.111269_b18) 2018; 5 Sinkhorn (10.1016/j.automatica.2023.111269_b21) 1967; 21 Notarnicola (10.1016/j.automatica.2023.111269_b17) 2020; 7
References_xml	– volume: 63 start-page: 347 year: 2020 end-page: 353 ident: b11 article-title: Distributed smooth convex optimization with coupled constraints publication-title: IEEE Transactions on Automatic Control – volume: 131 year: 2021 ident: b20 article-title: Subgradient averaging for multi-agent optimisation with different constraint sets publication-title: Automatica – volume: 32 start-page: 4752 year: 2022 end-page: 4770 ident: b24 article-title: Composite optimization with coupling constraints via dual proximal gradient method with applications to asynchronous networks publication-title: International Journal of Robust and Nonlinear Control – year: 2015 ident: b2 article-title: Convex optimization algorithms – volume: 27 start-page: 2597 year: 2017 end-page: 2633 ident: b14 article-title: Achieving geometric convergence for distributed optimization over time-varying graphs publication-title: SIAM Journal on Optimization – volume: 5 start-page: 1245 year: 2018 end-page: 1260 ident: b18 article-title: Harnessing smoothness to accelerate distributed optimization publication-title: IEEE Transactions on Control of Network Systems – volume: 59 start-page: 1524 year: 2014 end-page: 1538 ident: b5 article-title: Distributed constrained optimization by consensus-based primal-dual perturbation method publication-title: IEEE Transactions on Automatic Control – volume: 57 start-page: 151 year: 2012 end-page: 164 ident: b26 article-title: On distributed convex optimization under inequality and equality constraints publication-title: IEEE Transactions on Automatic Control – volume: 21 start-page: 343 year: 1967 end-page: 348 ident: b21 article-title: Concerning nonnegative matrices and doubly stochastic matrices publication-title: Pacific Journal of Mathematics – volume: 63 start-page: 1372 year: 2018 end-page: 1387 ident: b12 article-title: Distributed constrained optimization and consensus in uncertain networks via proximal minimization publication-title: IEEE Transactions on Automatic Control – volume: 54 start-page: 48 year: 2009 end-page: 61 ident: b15 article-title: Distributed subgradient methods for multi-agent optimization publication-title: IEEE Transactions on Automatic Control – volume: 61 start-page: 2718 year: 2013 end-page: 2723 ident: b13 article-title: D-ADMM: A communication-efficient distributed algorithm for separable optimization publication-title: IEEE Transactions on Signal Processing – volume: 55 year: 2010 ident: b16 article-title: Constrained consensus and optimization in multi-agent networks publication-title: IEEE Transactions on Automatic Control – year: 1999 ident: b1 article-title: Nonlinear programming – volume: 135 year: 2022 ident: b9 article-title: Distributed decision-coupled constrained optimization via Proximal-Tracking publication-title: Automatica – volume: 70 start-page: 523 year: 2021 end-page: 535 ident: b22 article-title: Distributed primal-dual method for convex optimization with coupled constraints publication-title: IEEE Transactions on Signal Processing – volume: 7 start-page: 483 year: 2020 end-page: 492 ident: b17 article-title: Constraint-coupled distributed optimization: A relaxation and duality approach publication-title: IEEE Transactions on Control of Network Systems – year: 1970 ident: b19 article-title: Convex analysis – volume: 46 start-page: 322 year: 2010 end-page: 329 ident: b25 article-title: Discrete-time dynamic average consensus publication-title: Automatica – volume: 39 start-page: 40 year: 2019 end-page: 72 ident: b10 article-title: Tutorial on dynamic average consensus: The problem, its applications, and the algorithms publication-title: IEEE Control Systems Magazine – volume: 84 start-page: 149 year: 2017 end-page: 158 ident: b6 article-title: Dual decomposition for multi-agent distributed optimization with coupling constraints publication-title: Automatica – volume: 117 year: 2020 ident: b7 article-title: Tracking-ADMM for distributed constraint-coupled optimization publication-title: Automatica – volume: 64 start-page: 3719 year: 2016 end-page: 3734 ident: b4 article-title: A proximal dual consensus ADMM method for multi-agent constrained optimization publication-title: IEEE Transactions on Signal Processing – volume: 5 start-page: 259 year: 2020 end-page: 264 ident: b8 article-title: A distributed dual proximal minimization algorithm for constraint-coupled optimization problems publication-title: IEEE Control Systems Letters – volume: 67 start-page: 144 year: 2016 end-page: 156 ident: b23 article-title: A decomposition method for large scale MILPs, with performance guarantees and a power system application publication-title: Automatica – year: 1989 ident: b3 publication-title: Parallel and distributed computation: Numerical methods – volume: 5 start-page: 1245 issue: 3 year: 2018 ident: 10.1016/j.automatica.2023.111269_b18 article-title: Harnessing smoothness to accelerate distributed optimization publication-title: IEEE Transactions on Control of Network Systems doi: 10.1109/TCNS.2017.2698261 – year: 2015 ident: 10.1016/j.automatica.2023.111269_b2 – volume: 55 issue: 4 year: 2010 ident: 10.1016/j.automatica.2023.111269_b16 article-title: Constrained consensus and optimization in multi-agent networks publication-title: IEEE Transactions on Automatic Control doi: 10.1109/TAC.2010.2041686 – volume: 63 start-page: 1372 issue: 5 year: 2018 ident: 10.1016/j.automatica.2023.111269_b12 article-title: Distributed constrained optimization and consensus in uncertain networks via proximal minimization publication-title: IEEE Transactions on Automatic Control doi: 10.1109/TAC.2017.2747505 – year: 1970 ident: 10.1016/j.automatica.2023.111269_b19 – volume: 61 start-page: 2718 issue: 10 year: 2013 ident: 10.1016/j.automatica.2023.111269_b13 article-title: D-ADMM: A communication-efficient distributed algorithm for separable optimization publication-title: IEEE Transactions on Signal Processing doi: 10.1109/TSP.2013.2254478 – volume: 5 start-page: 259 issue: 1 year: 2020 ident: 10.1016/j.automatica.2023.111269_b8 article-title: A distributed dual proximal minimization algorithm for constraint-coupled optimization problems publication-title: IEEE Control Systems Letters doi: 10.1109/LCSYS.2020.3001427 – volume: 54 start-page: 48 issue: 1 year: 2009 ident: 10.1016/j.automatica.2023.111269_b15 article-title: Distributed subgradient methods for multi-agent optimization publication-title: IEEE Transactions on Automatic Control doi: 10.1109/TAC.2008.2009515 – volume: 59 start-page: 1524 issue: 6 year: 2014 ident: 10.1016/j.automatica.2023.111269_b5 article-title: Distributed constrained optimization by consensus-based primal-dual perturbation method publication-title: IEEE Transactions on Automatic Control doi: 10.1109/TAC.2014.2308612 – volume: 32 start-page: 4752 issue: 8 year: 2022 ident: 10.1016/j.automatica.2023.111269_b24 article-title: Composite optimization with coupling constraints via dual proximal gradient method with applications to asynchronous networks publication-title: International Journal of Robust and Nonlinear Control doi: 10.1002/rnc.6048 – volume: 135 year: 2022 ident: 10.1016/j.automatica.2023.111269_b9 article-title: Distributed decision-coupled constrained optimization via Proximal-Tracking publication-title: Automatica doi: 10.1016/j.automatica.2021.109938 – volume: 57 start-page: 151 issue: 1 year: 2012 ident: 10.1016/j.automatica.2023.111269_b26 article-title: On distributed convex optimization under inequality and equality constraints publication-title: IEEE Transactions on Automatic Control doi: 10.1109/TAC.2011.2167817 – year: 1989 ident: 10.1016/j.automatica.2023.111269_b3 – volume: 84 start-page: 149 year: 2017 ident: 10.1016/j.automatica.2023.111269_b6 article-title: Dual decomposition for multi-agent distributed optimization with coupling constraints publication-title: Automatica doi: 10.1016/j.automatica.2017.07.003 – volume: 67 start-page: 144 year: 2016 ident: 10.1016/j.automatica.2023.111269_b23 article-title: A decomposition method for large scale MILPs, with performance guarantees and a power system application publication-title: Automatica doi: 10.1016/j.automatica.2016.01.006 – volume: 117 year: 2020 ident: 10.1016/j.automatica.2023.111269_b7 article-title: Tracking-ADMM for distributed constraint-coupled optimization publication-title: Automatica doi: 10.1016/j.automatica.2020.108962 – volume: 39 start-page: 40 issue: 3 year: 2019 ident: 10.1016/j.automatica.2023.111269_b10 article-title: Tutorial on dynamic average consensus: The problem, its applications, and the algorithms publication-title: IEEE Control Systems Magazine doi: 10.1109/MCS.2019.2900783 – volume: 131 year: 2021 ident: 10.1016/j.automatica.2023.111269_b20 article-title: Subgradient averaging for multi-agent optimisation with different constraint sets publication-title: Automatica doi: 10.1016/j.automatica.2021.109738 – volume: 7 start-page: 483 issue: 1 year: 2020 ident: 10.1016/j.automatica.2023.111269_b17 article-title: Constraint-coupled distributed optimization: A relaxation and duality approach publication-title: IEEE Transactions on Control of Network Systems doi: 10.1109/TCNS.2019.2925267 – volume: 27 start-page: 2597 issue: 4 year: 2017 ident: 10.1016/j.automatica.2023.111269_b14 article-title: Achieving geometric convergence for distributed optimization over time-varying graphs publication-title: SIAM Journal on Optimization doi: 10.1137/16M1084316 – volume: 21 start-page: 343 issue: 2 year: 1967 ident: 10.1016/j.automatica.2023.111269_b21 article-title: Concerning nonnegative matrices and doubly stochastic matrices publication-title: Pacific Journal of Mathematics doi: 10.2140/pjm.1967.21.343 – volume: 46 start-page: 322 issue: 2 year: 2010 ident: 10.1016/j.automatica.2023.111269_b25 article-title: Discrete-time dynamic average consensus publication-title: Automatica doi: 10.1016/j.automatica.2009.10.021 – year: 1999 ident: 10.1016/j.automatica.2023.111269_b1 – volume: 64 start-page: 3719 issue: 14 year: 2016 ident: 10.1016/j.automatica.2023.111269_b4 article-title: A proximal dual consensus ADMM method for multi-agent constrained optimization publication-title: IEEE Transactions on Signal Processing doi: 10.1109/TSP.2016.2544743 – volume: 70 start-page: 523 year: 2021 ident: 10.1016/j.automatica.2023.111269_b22 article-title: Distributed primal-dual method for convex optimization with coupled constraints publication-title: IEEE Transactions on Signal Processing doi: 10.1109/TSP.2021.3123888 – volume: 63 start-page: 347 issue: 1 year: 2020 ident: 10.1016/j.automatica.2023.111269_b11 article-title: Distributed smooth convex optimization with coupled constraints publication-title: IEEE Transactions on Automatic Control doi: 10.1109/TAC.2019.2912494
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